The purpose of the current research was to investigate the obstacles to the implementation of school-based management in Iran's educational system based on the interpretive structural modeling approach. The research method was a modeling study. The statistical population of the research was specifically the academic staff members of the university, 25 of whom were purposefully selected from the desired cases. The data collection tool was a researcher-made self-interactive questionnaire. In order to measure and evaluate the validity of the questionnaire, the criterion of content validity was used. The content validity of the questionnaire was 0.96. The data analysis was done with interpretive structural modeling method. The results of the research showed that 9 factors play a role as barriers to school-oriented management. Also, the results showed that financial obstacles (the cost of school-oriented management), socio-cultural obstacles and political obstacles (political focus on schools by the central government) as key independent variables have high influence power and low dependence. Also, the results showed that the lack of belief in the professional competence of school administrators, the lack of infrastructure facilities, the emphasis of upper management on the supervision and control of schools, and the lack of cooperation of local communities with school-based management as the linking variables with the greatest power of influence and the greatest power of dependence. and the centralism in the education system of the country and the lack of legal powers to school managers and staff as dependent variables have high dependency power and low influence power.

In the executive process of a tunneling project, overbreak phenomenon is always one of the most important issues. Nowadays, according to the progress of industry and having new technologies introduced to tunneling industry and their gradual acceptance, traditional methods (drilling and blasting) are replaced by the new methods. Although, the overbreak issue has been largely controlled by project implementers, but it has never been completely eliminated from tunnelling projects. In this research, prediction and optimization of overbreak was discussed using intelligent networks. Best model was selected based on scoring, then it was used for optimization. The R2 and RMSE values of the selected model were 0. 921, 0. 4820, 0. 923 and 0. 4277 for training and testing, respectively. The artificial bee colony (ABC) algorithm, which is one of the new optimization algorithms, was used to optimize these parameters of the blasing pattern. Due to the fact that over break is one of the main problems in tunneling, this reduction can have an important role in the quality and stability of the tunnel. After creating several optimization models and modifying its weights, the optimum amount for the overbreak was 1. 63 m2, which is 47% less than the lowest value achieved during execution process (3. 055 m2 ). The optimal pattern can be obtained with the least possible amount of overbreak.

In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex optimization problem that guarantees the global optimal solution. The convex optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Among the rules that jurisprudential scholars, jurisprudence, jurists, and scholars of rhetoric have investigated are their lexical roots and customary meanings and cited their opinions in this regard as a reason or preference. Rule: "Foundation Precedes Emphasis" is the one that in the interpretation prefers the new meaning to the repetition and emphasis on the old meaning in explaining the words, and considers the new effect and independent benefit of words better than emphasizing the previous meaning. The current research is descriptive and analytical in order to express the importance, position, capacity and how to use the aforementioned rule in different sciences and examples its comparative use has been shown in the interpretation of the Qur'an, principles of jurisprudence, law and vocabulary. In other words, the necessity of paying attention to the principles of jurisprudence stems from the fact that they are basic principles, a mechanism that helps in achieving the outcome of the work of the mujtahid and his aim in ijtihad what he strives for. The study leads to results, including this rule which is one of the branches of “the implementation of speech takes precedence over its neglect,” and that it aims to preserve speech from being abolished. It does not deal with the cases, in which, it is necessary to confirm or establish because of evidence where there is no justification for opposition or recommendation.

The Markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. Considering real world limits and conditions، the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. Therefore، the use of meta-heuristic methods such as neural networks and evolutionary algorithms has been an important issue in the literature of portfolio optimization. This study considers the problem of finding the efficient frontier associated with the standard mean-variance portfolio optimization model and presents a heuristic algorithm based upon particle swarm optimization for finding the cardinality constrained efficient frontier. The test data set is the daily prices of 20 companies from March 2006 to September 2008 from the TEPIX in Iran. The results show that PSO is successful in constrained portfolio optimization to find the optimum solutions in all levels of risk and return.

Bacterial foraging algorithm is one of the population-based optimization algorithms that used for solving many search problems in various branches of sciences. One of the issues discussed today is parallel implementation of population-based optimization algorithms on Graphic Processor Units. Due to the low speed of bacterial foraging algorithm in the face of complex problem and also lack the ability to solve large-scale problems by this algorithm, Implementation on the graphics processor is a suitable solution to cover the weaknesses of this algorithm. In this paper, we proposed a parallel version of bacterial foraging algorithm which designed by CUDA and has ability to run on GPUs. The performance of this algorithm is evaluated by using a number of famous optimization problems in comparison with the standard bacterial foraging optimization algorithm. The results show that Parallel Algorithm is faster and more efficient than standard bacterial foraging optimization algorithm.

In this paper, A innovative method designed to solving nonlinear optimization problems with convex object function and constrained. In this method, we define an cost function and we find variables to minimization of cost function. For create properly cost function we use K. K. T. optimal conditions. We used Nelder-Mead without derivative optimization method to minimization of cost function. When, dimensions of problem is about 10, application shows that efficiency of Nelder-Mead method is more than the other methods. Using new mathod is easier than the similar methods. By several examples efficiency of new method are verified.

In this paper, generalized model predictive spread control methodis developed to consider the intermediate constraints on system states and system inputs. Because of using the orthogonal basis functions and thus reducing the computational burden, this new method which is named constrained generalized model predictive spread control can be used in online implementation of a finite-time constrained optimal control problem. For demonstrating the performance of the proposed technique, in this paper an interceptor midcourse guidance problem is formulated to reach a desired point in space. Several constraints are considered such as: hard and soft intermediate and terminal constraints on system states and different constraints on input acceleration command to the interceptor in different time intervals of the trajectory. It is shown that in all the above situations, the proposed method could produce the optimal guidance commands such that all the interceptor trajectory constraints are satisfied.